Earticle

초록

영어

Studies are being conducted regarding falling recognition using sensors on smartphones to recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

목차

Abstract
1. Introduction
2. Related Works
2.1 Behavior Recognition Technique
2.2 Deep Learning
3. Design of Falling Recognition Application System Using Deep Learning
3.1 Deep Learning Model
3.2 System Architecture & Components
3.3 System Operation and Flow
4. Applying of System
5. Conclusion
References

키워드

저자

• TaeWoo Kwon [ Master, Department of Information System KwangWoon University Graduate School of Smart Convergence, Seoul 01897, Korea ]
• Jong-Yong Lee [ Professor, Ingenium College of liberal arts, KwangWoon University, Seoul 01897, Korea ]
• Kye-Dong Jung [ Professor, Ingenium College of liberal arts, KwangWoon University, Seoul 01897, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380